NVIDIA blasts Intel far having too many different AI architectures

Late yesterday evening I wrote about NVIDIA's excellent third-quarter results. Now it's time to take a look at the earnings call to check if the company made any interesting remarks.

In response to a question from an analyst, NVIDIA CEO Jen-Hsun Huang compiled his thoughts about why he thinks GPUs, and CUDA, are the ideal solution to tackle the artificial intelligence market. Huang said NVIDIA's strong suit is that they have a single architecture, and that customers can have a great deal of confidence that NVIDIA's platform will continue to receive support far into the future.

Huang pointed out that some other companies, take Intel for example, have four or five different architectures to support and that this means that some of these will eventually be dropped:

Jen-Hsun Huang
Yes, thank you, Vivek. So first of all, we have one architecture and people know that our commitment to our GPUs, our commitment to CUDA, our commitment to all of the software stacks that run on top of our GPUs, every single one of the 500 applications, every numerical solver, every CUDA compiler, every tool chain across every single operating system in every single computing platform, we are completely dedicated to it. We support the software first long as we shall live. And as a result of that the benefits to their investment in CUDA just continues to accrue. I -- you have no idea how many people send me notes about how they literally take out their old GPU, put in a new GPU. And without lifting a finger, things got 2x, 3x, 4x faster than what they were doing before, incredible value to customers. The fact that we are singularly focused and completely dedicated to this one architecture in an unwavering way allows everybody to trust us and know that we will support it for as long as we shall live, and that is the benefit of an architectural strategy.

When you have four or five different architectures to support that you offer to your customers and you ask them to pick the one that they like the best, you're essentially saying that you're not sure which one is the best. And we all know that nobody's going to be able to support five architectures forever. And as a result, something has to give and it would be really unfortunate for a customer to have chosen the wrong one. And if there's five architectures, surely, over time, 80% of them will be wrong. And so I think that our advantage is that we are singularly focused. With respect to FPGAs. I think FPGAs have their place. And we use FPGAs here at NVIDIA to prototype things and -- but FPGAs is a chip design. It's able to be a chip for -- it's incredibly good at being a flexible substrate to be any chip, and so that's it's advantage.

Our advantage is that we have a programming environment. And writing software is a lot easier than designing chips. And if it's within the domain that we focus on, like for example, we're not focused on network packet processing but we are very focused on deep learning. We are very focused on high performance and parallel numeric analysis. If we're focused on those domains, our platform is really quite unbeatable. And so that's how you think through that. I hope that was helpful.